Mathematics,
Journal Year:
2023,
Volume and Issue:
11(12), P. 2638 - 2638
Published: June 9, 2023
Blockchain
as
a
Service
(BaaS)
combines
features
of
cloud
computing
and
blockchain,
making
blockchain
applications
more
convenient
promising.
Although
current
BaaS
platforms
have
been
widely
adopted
by
both
industry
academia,
concerns
arise
regarding
their
performance,
especially
in
job
allocation.
Existing
allocation
strategies
are
simple
do
not
guarantee
load
balancing
due
to
the
dynamic
nature
complexity
execution.
In
this
paper,
we
propose
deep
reinforcement
learning-based
algorithm,
Balanced-DRL,
learn
an
optimized
strategy
based
on
analyzing
execution
process
jobs
set
scale
characteristics.
Following
extensive
experiments
with
generated
request
workloads,
results
show
that
Balanced-DRL
significantly
improves
achieving
5%
8%
increase
throughput
20%
decrease
latency.
Sustainability,
Journal Year:
2022,
Volume and Issue:
14(18), P. 11667 - 11667
Published: Sept. 16, 2022
The
amount
of
data
captured
is
expanding
day
by
which
leads
to
the
need
for
a
monitoring
system
that
helps
in
decision
making.
Current
technologies
such
as
cloud,
machine
learning
(ML)
and
Internet
Things
(IoT)
provide
better
solution
automation
systems
efficiently.
In
this
paper,
prediction
model
monitors
real-time
sensor
nodes
clinical
environment
using
algorithm
proposed.
An
IoT-based
smart
hospital
has
been
developed
controls
appliances
over
different
sensors
current
sensors,
temperature
humidity
sensor,
air
quality
ultrasonic
flame
sensor.
IoT-generated
have
three
important
characteristics,
namely,
real-time,
structured
enormous
amount.
main
purpose
research
predict
early
faults
an
IoT
order
ensure
integrity,
accuracy,
reliability
fidelity
IoT-enabled
devices.
proposed
fault
was
evaluated
via
tree,
K-nearest
neighbor,
Gaussian
naive
Bayes
random
forest
techniques,
but
showed
best
accuracy
others
on
provided
dataset.
results
proved
ML
techniques
applied
are
well
efficient
monitor
process,
considered
with
highest
94.25%.
could
be
helpful
user
make
regarding
recommended
control
unanticipated
losses
generated
due
during
process.
Electronics,
Journal Year:
2022,
Volume and Issue:
11(21), P. 3510 - 3510
Published: Oct. 28, 2022
Cloud
computational
service
is
one
of
the
renowned
services
utilized
by
employees,
employers,
and
organizations
collaboratively.
It
accountable
for
data
management
processing
through
virtual
machines
independent
end
users’
system
configurations.
The
usage
cloud
systems
very
simple
easy
to
organize.
They
can
easily
be
integrated
into
various
storages
incorporated
almost
all
available
software
tools
such
as
Hadoop,
Informatica,
DataStage,
OBIEE
purpose
Extraction-Transform-Load
(ETL),
processing,
reporting,
other
related
computations.
Because
this
low-cost-based
model,
users
utilize
services,
implementation
environment,
storage,
on-demand
resources
with
a
pay-per-use
model.
contributors
across
world
move
these
cloud-based
apps,
software,
large
volumes
in
form
files
databases
enormous
centers.
However,
main
challenge
that
cannot
have
direct
control
over
stored
at
do
not
even
know
integrity,
confidentiality,
level
security,
privacy
their
sensitive
data.
This
exceptional
property
creates
several
different
security
disputes
challenges.
To
address
challenges,
we
propose
novel
Quantum
Hash-centric
Cipher
Policy-Attribute-based
Encipherment
(QH-CPABE)
framework
improve
user’s
In
our
proposed
used
both
structured
unstructured
big
clinical
input
so
simulated
experimental
results
conclude
proposal
has
precise,
resulting
approximately
92%
correctness
bit
hash
change
96%
chaotic
dynamic
key
production,
enciphered
deciphered
time
compared
conventional
standards
from
literature.
Advances in medical technologies and clinical practice book series,
Journal Year:
2022,
Volume and Issue:
unknown, P. 117 - 136
Published: June 30, 2022
A
new
paradigm
for
the
solution
of
problems
involving
single-
and
multi-objective
fuzzy
linear
programming
is
presented
in
this
chapter.
As
opposed
to
complex
arithmetic
logic
intervals,
method
offered
uses
basic
mathematical
operations
integers
instead.
Using
numbers
express
variables
parameters
a
issue
(FLPP)
common.
However,
authors
only
talked
about
FLPP
with
here.
Triangular
are
used
as
parameters.
Ranking
functions
convert
into
clear
ones.
Crisp
optimization
techniques
have
been
used.
The
proposed
tested
on
variety
real-world
examples
that
address
both
these
concerns.
Measurement Sensors,
Journal Year:
2023,
Volume and Issue:
26, P. 100670 - 100670
Published: Jan. 10, 2023
Recent
advancements
in
the
Internet
of
Things
(IoT)
have
enhanced
quality
life
globally.
Billions
devices
are
brought
under
ambit
IoT
to
make
them
smarter.
IoT-based
applications
generating
voluminous
data
and
managing
this
widespread
amount
real-time
through
Cloud
Technology,
which
offers
high
computational
storage
facilities.
However,
sending
all
cloud
can
bring
serious
concerns
for
applications,
critical
require
instant
action
without
any
delay.
Edge
computing
has
recently
emerged
as
an
effective
technology
handle
processing
tasks
locally.
Additionally,
important
concern
networks
is
response
emergency
on
time
increase
performance
large-scale
systems.
As
such,
scheduling
becomes
vital,
where
non-emergency
be
prioritized
offload
nearby
edge
servers
respectively
enhance
Quality
Service
(QoS).
The
execution
order
allocating
resources
computation
avoid
delays
two
most
factors
that
must
addressed
during
task
Computing.
With
aforementioned
issues,
we
design
a
Priority
aware
Task
Scheduling
(PaTS)
algorithm
sensor
schedule
priority
servers.
problem
formulated
multi-objective
function
efficiency
proposed
evaluated
using
Bio-inspired
NSGA-2
technique.
overall
improvement
average
queue
delay,
time,
energy
obtained
200
17.2%,
7.08%
11.4%,
respectively.
results
show
significant
when
compared
with
benchmark
algorithms
demonstrating
effectiveness
solution.
Similarly,
comparative
increased
from
1000
also
shows
subsequent
improvements.
Expert Systems with Applications,
Journal Year:
2024,
Volume and Issue:
249, P. 123515 - 123515
Published: Feb. 17, 2024
The
online
bin
packing
problem
is
a
well-known
optimization
challenge
that
finds
application
in
wide
range
of
real-world
scenarios.
In
the
paper,
we
propose
novel
algorithm
called
FuzzyPatternPack(FPP),
which
leverages
fuzzy
inference
and
pattern-based
predictions
distribution
item
sizes
packing.
comparison
to
traditional
heuristics
like
BestFit(BF)
FirstFit(FF),
as
well
more
recent
PatternPack(PaP)
ProfilePacking(PrP)
based
on
predictions,
FPP
demonstrates
competitive
superior
performance
solving
various
benchmark
problems.
Particularly,
it
excels
addressing
problems
with
evolving
distributions,
making
promising
solution
for
applications
where
may
change
over
time.
This
research
unveils
potential
employing
logic
effectively
address
uncertainty
scheduling
planning
KSII Transactions on Internet and Information Systems,
Journal Year:
2022,
Volume and Issue:
16(6)
Published: June 30, 2022
With
the
massive
demand
and
growth
of
cloud
computing,
virtualization
plays
an
important
role
in
providing
services
to
end-users
efficiently.However,
with
increase
over
Cloud
Computing,
it
is
becoming
more
challenging
manage
run
multiple
Virtual
Machines
(VMs)
Computing
because
excessive
power
consumption.It
thus
overcome
these
challenges
by
adopting
efficient
technique
monitor
status
VMs
a
environment.Reduction
power/energy
consumption
can
be
done
managing
effectively
datacenters
environment
switching
between
active
inactive
states
VM.As
result,
energy
reduces
carbon
emissions,
leading
green
computing.The
proposed
Efficient
Dynamic
VM
Scheduling
approach
minimizes
Service
Level
Agreement
(SLA)
violations
manages
migration
lowering
along
balanced
load.In
work,
for
Dynamically
Migrated
(VMS-EDMVM)
first
detects
over-utilized
host
using
Modified
Weighted
Linear
Regression
(MWLR)
algorithm
dynamic
utilization
model
underutilized
host.Maximum
Power
Reduction
Reduced
Time
(MPRRT)
has
been
developed
selection
followed
two-phase
Best-Fit
CPU,
BW
(BFCB)
mechanism
which
simulated
CloudSim
based
on
adaptive
threshold
base.The
work
achieved
108.45
kWh,
total
SLA
violation
was
0.1%.The
count
reduced
2,202
times,
revealing
better
performance
as
compared
other
methods
mentioned
this
paper.
World Journal of Advanced Research and Reviews,
Journal Year:
2023,
Volume and Issue:
18(3), P. 970 - 992
Published: June 22, 2023
Information
Technology
(IT)
Disaster
Recovery
Planning
(IT
DRP)
and
Business
Continuity
(BC)
are
essential
components
of
an
organization’s
overall
resilience
strategy.
IT
DRP
focuses
on
the
recovery
restoration
systems,
infrastructure,
services
in
event
a
disruptive
incident
or
disaster,
aiming
to
minimize
downtime
data
loss.
BC,
other
hand,
encompasses
broader
perspective,
addressing
organization's
ability
maintain
operations
deliver
critical
during
after
disruption.
This
paper
provides
overview
highlighting
their
importance,
challenges,
strategies.
It
also
identifies
research
gaps
future
scope
these
areas.
The
findings
indicate
that
both
BC
face
challenges
effective
implementation.
These
include
evolving
nature
technology,
increasing
complexity
budget
constraints,
organizational
resistance
change,
need
for
skilled
personnel.
Overcoming
requires
comprehensive
understanding
risk
assessment,
development
robust
strategies
plans.
is
noted
despite
considerable
there
several
deserve
attention.
advanced
technologies
tools
more
efficient
continuity,
integration
with
management,
impact
emerging
such
as
cloud
computing
virtualization
strategies,
evaluation
effectiveness
cost-efficiency
different
